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Liyanachchi Mahesha Harshani De Silva; María Jesús Rodríguez-Triana; Irene-Angelica Chounta; Gerti Pishtari – Journal of Computing in Higher Education, 2025
With technological advances, institutional stakeholders are considering evidence-based developments such as Curriculum Analytics (CA) to reflect on curriculum and its impact on student learning, dropouts, program quality, and overall educational effectiveness. However, little is known about the CA state of the art in Higher Education Institutions…
Descriptors: Learning Analytics, Curriculum Evaluation, Higher Education, Stakeholders
Xia, Xiaona – Interactive Learning Environments, 2023
The research of multi-category learning behaviors is a hot issue in interactive learning environment, and there are many challenges in data statistics and relationship modeling. We select the massive learning behaviors data of multiple periods and courses and study the decision application of regression analysis. First, based on the definition of…
Descriptors: Learning Analytics, Decision Making, Regression (Statistics), Bayesian Statistics
Egle Gedrimiene; Ismail Celik; Antti Kaasila; Kati Mäkitalo; Hanni Muukkonen – Education and Information Technologies, 2024
Artificial intelligence (AI) and learning analytics (LA) tools are increasingly implemented as decision support for learners and professionals. However, their affordances for guidance purposes have yet to be examined. In this paper, we investigated advantages and challenges of AI-enhanced LA tool for supporting career decisions from the user…
Descriptors: Artificial Intelligence, Learning Analytics, Career Choice, Decision Making
Jean-Marie Gilliot; Madjid Sadallah – International Journal of Learning Technology, 2024
Learning analytics dashboards (LAD) deserve increasing attention, yet their adoption remains limited. Designing effective LAD is a difficult process, and LADs often fail in turning insights into action. We argue that providing explicit decision-making features in a participatory design process may help to develop LADs supporting action. We first…
Descriptors: Learning Analytics, Decision Making, Design, Participative Decision Making
Eirini Kalaitzopoulou; Athanasios Christopoulos; Paul Matthews – Informatics in Education, 2025
While research on Learning Analytics (LA) is plentiful, it often prioritises perspectives on LA systems over the practical ways instructors use data to analyse and refine the learning process per se. The present study addresses this inadequacy by investigating how student data is employed by educators in UK Higher Education Institutions (HEIs) and…
Descriptors: Information Literacy, Learning Analytics, Data Use, College Faculty
Marijn Martens; Ralf De Wolf; Lieven De Marez – Technology, Knowledge and Learning, 2025
Algorithmic decision-making systems such as Learning Analytics (LA) are widely used in an educational setting ranging from kindergarten to university. Most research focuses on how LA is used and adopted by teachers. However, the perspective of students and parents who experience the (in)direct consequences of these systems is underexplored. This…
Descriptors: Algorithms, Decision Making, Learning Analytics, Secondary School Students
Fabio Campos; Ha Nguyen; June Ahn; Kara Jackson – British Journal of Educational Technology, 2024
In this article, we offer theory-grounded narratives of a 4-year participatory design process of a Learning Analytics tool with K-12 educators. We describe how we "design-in-partnership" by leveraging educators' routines, values and cultural representations into the designs of digital dashboards. We make our long-term reasoning visible…
Descriptors: Learning Analytics, Kindergarten, Elementary Secondary Education, Teacher Attitudes
Xia, Xiaona; Qi, Wanxue – International Journal of Educational Technology in Higher Education, 2023
The temporal sequence of learning behavior is multidimensional and continuous in MOOCs. On the one hand, it supports personalized learning methods, achieves flexible time and space. On the other hand, it also makes MOOCs produce a large number of dropouts and incomplete learning behaviors. Dropout prediction and decision feedback have become an…
Descriptors: MOOCs, Dropouts, Prediction, Decision Making
Pargman, Teresa Cerratto; McGrath, Cormac; Viberg, Olga; Knight, Simon – Journal of Learning Analytics, 2023
The focus of ethics in learning analytics (LA) frameworks and guidelines is predominantly on procedural elements of data management and accountability. Another, less represented focus is on the duty to act and LA as a moral practice. Data feminism as a critical theoretical approach to data science practices may offer LA research and practitioners…
Descriptors: Learning Analytics, Responsibility, Feminism, Ethics
Rotem Abdu; Shai Olsher – Mathematics Teacher Education and Development, 2025
Group composition affects learning by individuals. Dialogic pedagogy approaches demonstrate that this is particularly true when each grouped student knows something others do not (i.e., "mutuality" grouping). Learning analytics can help grouping by providing teachers with data on students' content-specific learning. What are mathematics…
Descriptors: Mathematics Teachers, Grouping (Instructional Purposes), Learning Analytics, Mathematics Instruction
Isabel Hilliger; Constanza Miranda; Sergio Celis; Mar Pérez-Sanagustín – British Journal of Educational Technology, 2024
Several studies have indicated that stakeholder engagement could ensure the successful adoption of learning analytics (LA). Considering that researchers and tech developers may not be aware of how LA tools can derive meaningful and actionable information for everyday use, these studies suggest that participatory approaches based on human-centred…
Descriptors: Learning Analytics, Higher Education, Stakeholders, College Curriculum
Dalia Khairy; Nouf Alharbi; Mohamed A. Amasha; Marwa F. Areed; Salem Alkhalaf; Rania A. Abougalala – Education and Information Technologies, 2024
Student outcomes are of great importance in higher education institutions. Accreditation bodies focus on them as an indicator to measure the performance and effectiveness of the institution. Forecasting students' academic performance is crucial for every educational establishment seeking to enhance performance and perseverance of its students and…
Descriptors: Prediction, Tests, Scores, Information Retrieval
Teija Paavilainen; Sonsoles López-Pernas; Sanna Väisänen; Sini Kontkanen; Laura Hirsto – Technology, Knowledge and Learning, 2025
In digitalized learning processes, learning analytics (LA) can help teachers make pedagogically sound decisions and support pupils' self-regulated learning (SRL). However, research on the role of the pedagogical dimensions of learning design (LD) in influencing the possibilities of LA remains scarce. Primary school presents a unique LA context…
Descriptors: Learning Analytics, Independent Study, Elementary Education, Instructional Design
Kaveri, Anceli; Silvola, Anni; Muukkonen, Hanni – Journal of Learning Analytics, 2023
Learning analytics dashboard (LAD) development has been criticized for being too data-driven and for developers lacking an understanding of the nontechnical aspects of learning analytics (LA). The ability of developers to address their understanding of learners as well as systematic efforts to involve students in the development process are…
Descriptors: Personal Autonomy, Student Empowerment, Learning Analytics, Educational Technology
Pankaj Chejara; Luis P. Prieto; Yannis Dimitriadis; Maria Jesus Rodriguez-Triana; Adolfo Ruiz-Calleja; Reet Kasepalu; Shashi Kant Shankar – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) research has shown the feasibility of building automated models of collaboration quality using artificial intelligence (AI) techniques (e.g., supervised machine learning (ML)), thus enabling the development of monitoring and guiding tools for computer-supported collaborative learning (CSCL). However, the…
Descriptors: Learning Analytics, Attribution Theory, Acoustics, Artificial Intelligence

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